The T283 Team, by Mike Lang
Collaboration and fluidity dominates modern media work. A team of workers comes together for a project, only to disband again when it ends. Sure, packs of people may move together from project to project—just read through the credit rolls from Christopher Nolan’s films to identify some repeat offenders—but rarely does an entire team reassemble for another project down the road. Yet, despite the temporary nature of the work, in those grueling hours of the dreaded crunch, in the moments of hilarity and inspiration, in the moments of conflict and aggression, and even in the moments of absolute and total boredom, media workers form relationships with roots so deep they sustain for a lifetime. For Shannon Schenck, Matt Falk, Brian Steward, and Sophie Parkison, the associate instructors for T283: Introduction to Production Techniques and Practice the reality of media work holds true for work as an AI.
The conference room feels like the principal’s office Brian jokes. “I feel like I’m about to get scolded.” The beige walls and lack of windows certainly don’t produce a warm fuzzy feeling, but a good-natured vibe pervades none the less. With these four plus T283 crew chief John Walsh, location doesn’t matter that much. They can make anything fun. I’m fortunate because we have managed to find a time when everyone can meet. Anybody who has ever tried to schedule/reschedule an event with a group of graduate students and faculty members knows how difficult this can be. As an MA student I rarely interact with the production side of the department, so I’m excited to finally pull back the curtain and see what actually goes on. “This better be good” jokes Matt, “This is the only reason I put on pants today.”
T283 is a hands-on production course that gives students opportunities to work with the equipment and software they will be using in the field, in environments that simulate real-life working conditions. As Sophie notes, T283 acts as a sampler, exposing students to the range of jobs one would encounter in a real studio or in real projects. T283 features two parts. Every Monday from 2:30-3:45 the 90 or so students roll into the lecture portion of the class led by John Walsh. Composed mostly of second semester sophomores and juniors, T283 is a make or break class for students hoping to continue along the production trajectory, and as a result, it features a lengthy waiting list and a number of students who have waited semesters to get in. In addition to the lecture, students must attend a four hour lab led by one of the AIs. Each of the eight sections contains 10-14 students. While older iterations of T283 were broadcast production oriented and featured eight weeks of studio work, and eight weeks of work in the field, John Walsh and Ron Osgood have introduced new elements to the course. In addition to studio and field, there is a section of new media. With Photoshop and Dreamweaver skills acquired in the course , at the end of the semester students should be able to put together a professional online portfolio that features the work they have done in both the studio and the field.
Because the bulk of the class takes place in the lab, the success or failure of the course largely rides on the AIs. Each lab has a distinct personality, according to Brian, and figuring out how to work with those different dynamics is a big part of the job. As Matt says, the AIs have to play the role of executive producer. They have to put everyone in the best position to succeed, and that can’t happen if the AIs don’t know the students. You have to know what makes them tick, what is going on in their lives, and what is their personality because it is all going to come up in their work. But then, with such small classes, and four hours of face time in the lab, “you’re going to learn them really fast,” says Shannon. Because of the structure of the course, the relationship between AI and student extends much further than that of the typical instructor-student relationship. As Shannon says, because the AIs invest so much in their students, their students invest back in them. They come to the AIs to talk about life, classes, projects outside of class, equipment, and everything in between. It creates a different dynamic in the classroom. The students really value what you think. Matt says the system builds trust. “Other students see us laughing and joking back and forth, which encourages them to open up to us.” Beyond grading and giving feedback, the AIs have to foster a sense of collaboration and creativity that encourages students to really engage and think.
The beauty of the course lies in the subtleties. While the course covers all of the basics, the difference between average and exceptional can sometimes amount to half a second. For Brian, the moments students learn these subtleties are light bulb moments. He says one should not tell students what to do but to let them attain realizations on their own. In one instance, one of Brian’s students was directing a scene. Instead of watching the monitors as the scene played out, the student had his head buried in the script, calling out camera changes based on the dialogue. After a few poor takes, Brian walked up, and took the script out of his hand and told them to roll again. As soon as the take started, the light bulb clicked on and the student understood immediately why watching the monitors is so important. In the span of five minutes, the student recorded the best take of the day, and gained a whole new confidence in one of the most intimidating positions in the studio. In a sense the course is an exercise in building confidence, and for the AIs nothing beats a student who comes in nervous and afraid and leaves bustling with energy and self-assurance. As Brian notes, sometimes you might suggest an idea to a student who will muster up the courage to say, “I think I’m going to stick with my idea and see how it goes,” and when it turns out better than the suggestion, you know they are really getting it.
The AIs work as a team and rely on each other like family. As John notes, every member of the AI team possesses a different yet complimentary set of skills and experiences: Shannon’s handiwork with the camera, knowledge of the production lab, and background in teaching screen writing; Matt’s masterful command of audio, and experience as a documentary filmmaker; Brian’s background in the industry (if you haven’t check out Brian’s IMDB page yet, make it happen); Sophie’s knowledge of story and development and her extensive experience with Studio 5 and IU in general. As such, the AIs lean on each other in various circumstances. Matt is a common fixture in labs that aren’t his own—talking about the soundboard and sharing his extensive audio knowledge. Brian may come over to students working in field to demonstrate techniques or share his own experiences. Since Brian hadn’t set foot in studio 5 since the first Reagan administration (when he was an undergrad), he relied on his fellow AIs to show him everything in the studio. They even taught him how to use Final Cut. They also lean on each other when it comes to dealing with students. The boundaries which separate one AI’s students from another are very porous. They constantly field questions and review work from students in other labs, especially if they are hanging around the production lab. “You have to be careful” says Sophie. “If you go in, you might not come out.”
The team is in constant contact over email, at their weekly meetings on Monday, and as they cross paths between labs. They share strategies, discuss what went well, and ways to make things better. Most importantly, they encourage one another. “It’s almost like we’re soldiers together” says Shannon, and they certainly share that camaraderie. Brian and his wife Elizabeth are expecting expecting in April, yet the team has already devised a contingency plan in the event the baby is early, late, or on time. They take care of one another and even though they are providing their students with a real media work experience, they are also getting one themselves. “This is how you feel about a crew when you work with a crew” says John. “Its our semi-permanent work group!” jokes Sophie.
Each semester is different. AI teams come and go, group dynamics change, and new concepts are taught, but T283 continues to offer students an experience of media work that reflects the real world, and without the exceptional work of the AIs, none of that is possible, a fact not lost on the students. At the end of the fall semester Brian surprised his lab with pizza. As his wife Elizabeth walked into the studio with the stack of boxes, the students had a surprise of their own. Knowing the newlyweds were expecting, the students had pooled their money together to purchase a gift of their own. From a pile of baby clothes, one of the students pulled out a tiny onesie that read “Daddy’s Little Sweetheart.” That just doesn’t happen elsewhere.
John Walsh frequently refers to his AI team as superheroes. After my conversation with them, it is easy to see how important they are to the success of our program.
Ryland’s Stats Search, by Mike Lang
Ryland Sherman, first-year Ph.D. student, has plenty of experience with statistics. While this author humbly admits a lack of in-depth knowledge in statistics, it’s still safe to say that “proof-based multivariate calculus” sounds daunting—and, in the very first class of Ryland’s undergrad career, proficiency in it was expected before walking through the door. When in law school, he took a business class: Spreadsheet Modeling in Finance, a synthesis of “multivariate calculus, economics, finance and inter-temporal math, and statistics.” Ryland earned an “A,” impressive not only because of the material, but also because the bar for that top grade was set at ninety-six percent. The point is, simply, that one Ryland Sherman is no slouch when it comes to statistics. A self-proclaimed guru in Excel, he also knows most of those acronym-named stats programs that begin with the letter “S.” Then, he met a new letter of the alphabet, R—“the Linux of stats,” according to Ryland—and the experience has caused him to give pause when considering his next methods class.
Most Telecom students take applied stats courses, often in the psychology department. Ryland, however, decided to go to the Department of Statistics to attain a more abstract, fundamental grasp of statistics. The students in the S501: Statistical Methods I were asked to vote for the program of choice and they chose R. Though he prefers Excel, “ultimately, R is more robust,” Ryland explained. “It’s able to run these packages that were created by statisticians on this freeware, shared among people who must be advancing their careers by writing open-source R code to do cutting-edge statistical stuff. That’s why stats majors love R—but stats majors have computer programming backgrounds, apparently.” R is not for first-time programmers; it has a reputation for being clunky and sometimes outright counterintuitive. Nicky Lewis, another member of our cohort, took the class previously and did well—but she had a background in HTML programming. “Right off the bat, we were expected to be able to learn new programming languages and run loops,” Ryland said. Instead the course material ran loops around him.
“I have a love-hate relationship with R,” Ryland confessed. “She’s a rough mistress, hard to read and hard to understand. Occasionally, I was able to reach a mutually agreeable outcome—often at three or four in the morning, long after I thought I would be done.” As with most relationships, it was difficult to see the issues before diving into it. Without any background in programming, it became difficult for Ryland to learn the stats-related lessons of the course. “Programming is a world of trial and error,” Ryland said, “where you spend most of your time fixing a problem you didn’t see was there. That’s not a way to learn stats.”
“While I think everybody needs to know basic stats and be able to draw from that toolkit, I think that there are lots of areas of equations and models that can be pulled from areas other than the statistics program,” Ryland said. “On some level, I’m happy that R slapped me around a bit, because it’s made me think more outside the box.” Forced to pick a new minor, he is considering economics, sociology, and informatics. Regardless of which department he chooses, from now on, statistics will be less of an abstract affair. “Stats does not exist independent of the way it is used. The reason why so many people in our program have taken stats in psychology is that stats is taught in the context of psychological methods … putting stats in context is much more valuable. The statistical methods utilized by people coming out of psychology stats are as sophisticated as anything else and are a much better, custom fit to their applications.”
Russell’s Thesis, by Ken Rosenberg
Russell McGee and Brad Cho, both second-semester master’s students and experienced filmmakers, are going to collaborate on a project of thesis-level proportions. Cinema 67 (working title) is a postmodern coming-of-age movie that deals with intolerance of homosexuality in a small rural town. Some of the more lighthearted elements, like a prank involving cotton candy dye, are loosely derived from Russell’s past experiences working at a drive-in theater. Brad has been commissioned as the director of cinematography. This project will be a fresh and exciting undertaking for Brad, as his past experience has mainly been with documentaries. With the script complete and a tentative schedule in place, they are in the process of finalizing the cast and building sets—shooting will begin over the summer. If you want to provide encouragement—or maybe a headshot, depending on your intended career trajectory—feel free to stop them in the hall for a quick chat about their work. Stay tuned for further updates!
Random Photo of the Week: The Ted
Ted Jamison-Koenig's new vanity plate finally offers the department a way to distinguish between the student and the professor in casual conversation.
We are all kinda here: Collaborating in virtual and analog environments
Over the past few months, I have been assisting Dr. Anne Massey (Dean’s Research Professor & Professor of Information Systems) and a team of researchers with a National Science Foundation Grant. This grant studies collaborative virtual presence (CVP) in collaborative virtual environments (CVE), such as Second Life. Using a range of measurements (SL activity, eye tracking and physiological) and researchers from a number of areas (Telecommunications, Information Systems, HPER) this project is, in itself, a collaborative effort that synchronously captures three streams of data. I will give an overview of the project, its goals and the part I am playing.
Reconceptualizing Gatekeeping in Multimodal Contexts: The Case of Italian Radiovision RTL 102.5
A change is occurring in media production and consumption in mass media contexts that affects the gatekeeping process of content selection: User-generated content (UGC) is increasingly being incorporated into programming. This research asks: What are the differences between attitudes and practices with regards to UGC integration in mass media programming, and what are the actual audience participation patterns? To address these questions, gatekeeping theory is applied to a case study of an interactive multimedia setting — a leading Italian radio-television-web station, station RTL 102.5. Through interviews with media producers and content analysis, this study analyzed two types of UGC: SMS messages and Facebook messages.
Mark Bell is a PhD candidate at Indiana University in the Department of Telecommunications. His past research has focused on virtual words but more recent work focuses on deception in computer mediated environments. He is interested in digital deception detection, group information verification, digital image and video manipulation and online identity manipulation.
Asta Zelenkauskaite is a Ph.D. candidate at the Department of Telecommunications, Indiana University. Her research interests include Computer-Mediated Communication, and Social Media. She researched user-generated content mediated by TV such as Facebook messages and mobile texting; user participation pattertns in online environment – online Internet Relay Chat; collaboratevely analyzed knowledge depositories such as Wikipedia and user interaction patterns in an online massively multiplayer game BZFlag.
The audio from last Friday’s seminar: Brown bag 6 (Feb. 24, 2012 – Asta and Mark)